Reference Guide

3-176 Full Command and Function Reference
Access: …µ PR 1
Flags: I/O Device (–33), Printing Device (–34), Double-spaced Printing (–37), Linefeed (–38), I/O
Device for Wire (–78). If flag –34 is set, flag –33 must be clear.
Input/Output:
Level 1/Argument 1 Level 1/Item 1
object
→
object
See also: CR, DELAY, OLDPRT, PRLCD, PRST, PRSTC, PRVAR
PREDV
Type: Command
Description: Predicted y-Value Command: Returns the predicted dependent-variable value y
dependent
, based on
the independent-variable value x
independent
, the currently selected statistical model, and the current
regression coefficients in the reserved variable ΣPAR.
PREDV is the same as PREDY. See PREDY.
Access: …µ PREDV
Input/Output:
Level 1/Argument 1 Level 1/Item 1
x
independent
→
y
dependent
See also: PREDY
PREDX
Type: Command
Description: Predicted x-Value Command: Returns the predicted independent-variable value x
independent
, based
on the dependent-variable value y
dependent
, the currently selected statistical model, and the current
regression coefficients in the reserved variable ΣPAR.
The value is predicted using the regression coefficients most recently computed with LR and
stored in the reserved variable ΣPAR. For the linear statistical model, the equation used is this:
y
dependent
= (mx
independent
) + b
where m is the slope (the third element in ΣPAR) and b is the intercept (the fourth element in
ΣPAR).
For the other statistical models, the equations used by PREDX are listed in the LR entry.
If PREDX is executed without having previously generated regression coefficients in ΣPAR, a
default value of zero is used for both regression coefficients, and an error results.
Access: …µ PREDX
Input/Output:
Level 1/Argument 1 Level 1/Item 1
y
dependent
→
x
independent
Example: Given five columns of data in ΣDAT, the command sequence:
2 XCOL 5 YCOL LOGFIT LR 23 PREDX
sets column 2 as the independent variable column, sets column 5 as the dependent variable
column, and sets the logarithmic statistical model. It then executes LR, generating intercept and
slope regression coefficients, and storing them in ΣPAR. Then, given a dependent value of 23, it
returns a predicted independent value based on the regression coefficients and the statistical
model.
See also: COLΣ, CORR, COV, EXPFIT, ΣLINE, LINFIT, LOGFIT, LR, PREDY, PWRFIT, XCOL,
YCOL